oru.sePublikationer
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Volatility leverage autoregressive models with non-Gaussian innovations
Örebro University, Örebro University School of Business. (Statistik)ORCID iD: 0000-0002-1488-4703
Department of Statistics, Lund University, Lund, Sweden. (Statistik)
(English)Manuscript (preprint) (Other academic)
Abstract [en]

In this article we discuss the non-Gaussian alternatives to model financial volatility. The comparison has been made between two special cases of the GH distributions. We derive the stationarity conditions, moments, dependence structure to account for heavy tails and leverage in the data and discuss several estimation strategies to the proposed non-Gaussian model. Finally through empirical investigation the model efficiency has been evaluated using real data.

Keyword [en]
Generalized asymmetric Laplace, Gamma variance distribution, GARCH, Volatility, Leverage
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:oru:diva-57935OAI: oai:DiVA.org:oru-57935DiVA: diva2:1106327
Available from: 2017-06-07 Created: 2017-06-07 Last updated: 2017-06-20

Open Access in DiVA

No full text

Search in DiVA

By author/editor
Javed, Farrukh
By organisation
Örebro University School of Business
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar

Total: 10 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf